Updates

Model and report changes

  1. We have extended the use of serological sampling data to use samples taken beyond the first wave of the pandemic. The samples are those collected by NHS Blood and Transplant using the Roche-N assay, which measures the prevalence of infection-acquired antibodies in the population.
  2. The model now accounts for the ongoing immunisation programme, stratifying the population of people still susceptible to infection with the virus according to their immunisation status (unimmunised/1 dose/2 doses). We use data on the daily proportions of the population getting immunised to inform this splitting of the population, assuming that it takes three weeks for vaccine-derived immunity to develop. Vaccine efficacy is assumed against both infection and death, using values for the efficacy in agreement with those found here. We have a changepoint in the vaccine efficacy on the 10th May, which marks a transition from alpha being the dominant variant, to delta.
  3. The model also accounts for a different susceptibility to infection in each adult age group (no prior information is used); and for the under-15s, (using prior information from Viner et al, 2020, which estimates children to be less likely to acquire infection when in contact with an infectious individual).
  4. The model has the ability to incorporate estimates of community prevalence, by region and age group, from the Office of National Statistics COVID-19 Infection Survey (see Data Sources for details). These are included weekly since the outset of the Survey in May 2020 for the age groups >4 years to inform trends in incidence that are too recent to be captured by the data on deaths.
  5. The underlying probability of an unvaccinated individual dying following infection with SARS-CoV2 (the infection-fatality rate, IFR) is allowed to change gradually over the course of 30 days every (approximately) 100 days. This is designed to reflect fluctuations due to seasonal effects, demand on healthcare services or the emergence of new virus variants of differing severity.
  6. The ‘Epidemic summary’ only reports the current value for the IFR by age. To visualise how this has changed over time in our model, see the IFR tab in the ‘Infections and Deaths’ section of the report. The quantity that is now plotted under this tab is the probability of dying if infected, taking into account the impact of the immunisation programme - it is an average of a lower rate of death in vaccinated individuals and a higher rate among the unvaccinated.

Updated findings

  1. The estimated number of new daily infections on the 26th November across England is 50,300 (43,500–57,600, 95% credible interval). The daily infection rate is estimated to be 90 per 100k population per day nationally. The highest rate is in the North East (NE) with 153 infections per 100K population followed by the East Midlands (EM) at 148 and the South East (SE) at 105. These rates correspond to 4,080, 7,110 and 9,600 daily infections, respectively. In most of the remaining regions rates are around 80 per 100K population (East of England (EE), West Midlands (WM), London (GL) and the South East (SE)) while lowest at around 50 in the North West (NW) and Yorkshire and Humber (YH). Note that a substantial proportion of these infections will be asymptomatic.
  2. The daily number of deaths is declining, and we forecast between 105 and 174 deaths per day by the 17th of December, slightly higher than what we predicted last week.
  3. This week it is unlikely that Rt is bigger than 1, with a reasonable chance only in the NE, SE (55% and 45% respectively). For everywhere else, the chance of Rt being above 1 is around 10% or less.
  4. The growth rate for England remains at -0.01 (-0.02– 0.00) per day. This means that, nationally, the number of infections is decreasing, corresponding to an Rt of around 0.9, consistent with last week’s results.
  5. Our estimates for the attack rate, that is the proportion of the regional populations who have ever been infected, have NE at 59% and GL at 56%. WM, YH and NW are all also above the national average with 53%, 49% and 50% respectively.The SE and SW continue to have the lowest attack rates at 37% and 36%. These are consistent with last week’s estimates.
  6. Note that the deaths data used are only very weakly informative on Rt over the last two weeks. Therefore, the estimate for current incidence, Rt and the forecast of daily numbers of deaths are likely to be subject to some revision.

Interpretation

Our estimates show a pandemic with Rt values estimated mainly to remain below 1. We can now confirm that this fall in transmission has percolated through to the deaths, with the number of deaths occurring daily having peaked in the first week of November.

Plots of the IFR over time show that from the end of January we estimate a decreasing IFR in all adult age groups, but most steeply in the older ages. This drop indicates the benefits of immunisation against death over and above the benefits against infection. Following this drop, there has been a period of plateau followed by a gradual increase in the overall IFR to 0.3% (0.29%–0.31%). However, the age-specific IFRs appear to be falling, suggesting that the overall increase is due to shifting age patterns towards older people being infected. The estimated IFR is highest in the over-75s at 3.4% (3.3%–3.7%)

For context, in addition to the data used here, the number of reported new positive cases (by date of specimen) is very slightly increasing. As a caveat to this, trends in the number of reported cases are highly dependent on the volume and targeting of testing, the public’s testing behaviour and significant reporting delays, and therefore are difficult to interpret. Overall, there have been 8.7million positive tests, which, compared to our estimate of cumulative incidence, would suggest that, overall, around 1 in 3 infections have been identified. This seems plausible, particularly when considering the low ascertainment rates of the first wave. Admissions to hospitals have been falling in number, and the prevalence of infection, as estimated by the ONS Coronavirus Infection Survey, remains stable around 1.6% in England, while showing some slight increasing trends in some regions.

Summary

Real-time tracking of an epidemic, as data accumulate over time, is an essential component of a public health response to a new outbreak. A team of statistical modellers at the MRC Biostatistics Unit (BSU), University of Cambridge, are working to provide regular now-casts and forecasts of COVID-19 infections and deaths. This information feeds directly to the SAGE sub-group, Scientific Pandemic Influenza sub-group on Modelling (SPI-M), and to regional Public Health England (PHE) teams.

Methods

We fit a transmission model (Birrell et al. 2020) to a number of data sources (see ‘Data Sources’), to reconstruct the number of new COVID-19 infections over time in different age groups and NHS regions, estimate a measure of ongoing transmission and predict the number of new COVID-19 deaths.

Data sources

We use:

  1. Data on COVID-19 confirmed deaths from the Public Health England (PHE) line-listing This consists of a combination of deaths notified to:
    • the Demographics Batch Service (DBS), a mechanism that allows PHE to submit a file of patient information to the National Health Service spine for tracing against the personal demographics service (PDS). PHE submit a line list of patients diagnosed with COVID-19 to DBS daily. The file is returned with a death flag and date of death updated (started 20th March, 2020).
    • NHS England, who report data from NHS trusts relating to patients who have died after admission to hospital or within emergency department settings.
    • Health Protection Teams (HPTs), resulting from a select survey created by PHE to capture deaths occurring outside of hospital settings, e.g. care homes (started 23rd March, 2020)
  2. Data on antibody prevalence in blood samples from a PHE survey of NHS Blood Transfusion (NHSBT) donors.

Data are stratified into eight age groups: <1, 1-4, 5-14, 15-24, 25-44, 45-64, 65-74, 75+, and the NHS England regions (North East and Yorkshire, North West, Midlands, East of England, London, South East, South West).

  1. Published information on the the natural history of COVID-19 (Verity et al., 2020; Li et al, 2020)
  2. Information on contacts between different age groups from:
    • A Survey that describes relative rates of contacts between different age groups (Mossong et al. 2008).
    • Google Community Mobility reports, informing the changes in people’s mobility over the course of the pandemic, particularly after the March 23rd lockdown measures.
    • The ONS’ time use survey, which in conjunction with the google mobility study, allows estimation of the changing exposure to infection risk over time.
    • Data from the Department for Education describing the proportion of children currently attending school.
  3. Daily data on the numbers of people getting immunised by age-group and region. These data are derived from the National Immunisation Management Service (NIMS). These data includes all COVID-19 immunisations administered at hospital hubs, local immunisation service sites such as GP practices, and dedicated immunisation centres.

Epidemic summary

Current \(R_t\)

Value of \(R_t\), the average number of secondary infections due to a typical infection today.

Number of infections

Attack rate

The percentage of a given group that has been infected.

By region

By age

Current IFR

Change in infections incidence

Growth rates

NB: negative growth rates are rates of decline. Values are daily changes.

Region Median 95% CrI (lower) 95% CrI (upper)
England -0.01 -0.02 0.00
East of England -0.02 -0.04 0.00
East Midlands -0.01 -0.02 0.01
London 0.00 -0.02 0.01
North East 0.00 -0.02 0.02
North West -0.01 -0.03 0.01
South East 0.00 -0.02 0.01
South West -0.02 -0.05 -0.01
West Midlands -0.02 -0.04 0.00
Yorkshire and The Humber -0.03 -0.05 -0.01

Halving times

Halving times in days, if a region shows growth than value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England 75.55 44.71 248.83
East of England 35.02 16.85 267.39
East Midlands 81.69 28.02 NA
London 181.94 37.32 NA
North East NA 39.63 NA
North West 65.44 22.15 NA
South East 633.62 42.37 NA
South West 28.53 13.51 94.13
West Midlands 30.79 16.50 271.94
Yorkshire and The Humber 21.00 12.48 49.10

Doubling times

Doubling times in days, if a region shows decline then the value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England NA NA NA
East of England NA NA NA
East Midlands NA 93.80 NA
London NA 58.75 NA
North East 462.67 36.51 NA
North West NA 92.72 NA
South East NA 54.24 NA
South West NA NA NA
West Midlands NA NA NA
Yorkshire and The Humber NA NA NA

Change in deaths incidence

Growth rates

NB: negative growth rates are rates of decline. Values are daily changes.

Region Median 95% CrI (lower) 95% CrI (upper)
England 0.00 0.00 0.01
East of England 0.00 -0.02 0.01
East Midlands 0.01 0.00 0.02
London 0.00 -0.01 0.02
North East 0.02 0.00 0.03
North West 0.00 -0.02 0.01
South East 0.01 -0.01 0.02
South West -0.01 -0.03 0.00
West Midlands -0.01 -0.02 0.01
Yorkshire and The Humber -0.02 -0.03 0.00

Halving times

Halving times in days, if a region shows growth than value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England NA 158.38 NA
East of England 176.42 39.30 NA
East Midlands NA 226.38 NA
London NA 79.34 NA
North East NA NA NA
North West 206.81 41.13 NA
South East NA 94.91 NA
South West 62.31 26.71 NA
West Midlands 96.04 35.67 NA
Yorkshire and The Humber 40.44 24.08 218.24

Doubling times

Doubling times in days, if a region shows decline then the value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England 1515.13 127.95 NA
East of England NA 66.42 NA
East Midlands 71.52 28.89 NA
London 200.27 40.20 NA
North East 42.01 20.12 1393.72
North West NA 59.94 NA
South East 122.57 35.21 NA
South West NA 330.47 NA
West Midlands NA 80.09 NA
Yorkshire and The Humber NA NA NA
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Infections and deaths

The shaded areas show periods of national lockdown, the green lines the dates (once confirmed) of the steps in the roadmap in the UK Governement’s COVID-19 Response – Spring 2021, and the red line shows the date these results were produced (26 Nov).

Infection incidence

By region

By age

Cumulative infections

By region

By age

Deaths incidence

By region

By age

Cumulative deaths

By region

By age

IFR

Prob \(R_t > 1\)

The figure below shows the probability that \(R_t\) is greater than 1 (ie: the number of infections is growing) in each region over time. Clicking the regions in the legend allows lines to be added or removed from the figure.

\(R_t\)

Copyright © MRC Biostatistics Unit, University of Cambridge